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作 者:刘伟 Liu Wei(GuiZhou University Institute of Engineering Investigation&Design Co.,Ltd.,Guiyang 550025,China)
机构地区:[1]贵州大学勘察设计研究院有限责任公司,贵阳550025
出 处:《绿色建造与智能建筑》2024年第12期125-127,183,共4页Green Construction and Intelligent Building
摘 要:建筑电气系统异常故障在线诊断方法直接对故障异常信号进行高维特征解析未对建筑电气系统运行数据进行采样,造成方法故障诊断效果差,因此,提出基于LS-SVM的建筑电气系统异常故障在线诊断。对建筑电气系统运行数据进行采样,根据采样结果对故障异常信号进行特征解析,最后基于LS-SVM实现系统故障分类检测。实验结果表明该研究方法在诊断系统故障时漏报率更低,诊断效果更好。The online fault diagnosis method of building electrical system abnormal fault directly carries out high-dimensional feature analysis of fault abnormal signal without sampling the operating data of building electrical system,resulting in poor fault diagnosis effect of the method.Therefore,an online fault diagnosis method of building electrical system abnormal fault based on LS-SVM is proposed.The running data of the building electrical system is sampled,and the fault anomaly signal is analyzed according to the sampling results.Finally,the system fault classification detection is realized based on LS-SVM.The experimental results show that this method has lower false report rate and better diagnostic effect.
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